CVE-2026-71446 in ail-framework
Summary
by MITRE • 08/07/2026
AIL Framework contains a stored cross-site scripting vulnerability in the crawler domain view. Crawled URLs were embedded directly into the JavaScript onclick handler used to display a stored screenshot, without context-appropriate encoding.
An attacker who can cause a specially crafted URL to be recorded in the crawler history can inject JavaScript syntax into the stored URL value. The payload remains stored by AIL and is subsequently included in the domain view. When an authenticated analyst clicks the screenshot icon associated with the malicious URL, the injected JavaScript executes in the analyst’s browser within the security context of the AIL Framework application.
Successful exploitation could allow an attacker to access information available to the analyst’s session, modify displayed content, or perform application actions using the analyst’s privileges. Exploitation requires the victim to interact with the affected screenshot entry.
The vulnerability was corrected by serializing the crawled URL with Jinja’s tojson filter before inserting it into the JavaScript handler. This safely escapes characters that could otherwise terminate the JavaScript string and introduce executable code.
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Analysis
by VulDB Data Team • 08/07/2026
This vulnerability resides within the AIL Framework's crawler domain view functionality, representing a classic stored cross-site scripting flaw that demonstrates poor input validation and output encoding practices. The security issue stems from the framework's handling of crawled URLs that are directly embedded into JavaScript onclick handlers without proper context-appropriate encoding, creating an environment where malicious payloads can persist and execute. The vulnerability is categorized under CWE-79 as a failure to sanitize output before it is returned to users, specifically manifesting in the JavaScript context where unescaped data can be interpreted as executable code rather than mere text.
The technical exploitation occurs through a carefully crafted URL that, when recorded in the crawler history, contains malicious JavaScript within its value. When an authenticated analyst interacts with the affected interface by clicking on the screenshot icon associated with this malicious entry, the embedded payload executes within the analyst's browser session, operating under the security context of the AIL Framework application. This privilege escalation scenario is particularly concerning because it leverages the analyst's authenticated session to perform actions that would otherwise be restricted to legitimate users. The attack requires user interaction through the specific screenshot icon click, making it a client-side exploitation vector that aligns with ATT&CK technique T1566.001 for initial access via spearphishing attachments or links.
The operational impact of this vulnerability extends beyond simple information disclosure, as it could enable attackers to perform actions within the application using analyst privileges, potentially leading to data manipulation, unauthorized access to sensitive information, or even lateral movement within the security infrastructure. The stored nature of the vulnerability means that once exploited, the malicious payload remains persistent and can affect multiple users who interact with the affected interface. This type of vulnerability is particularly dangerous in security frameworks where analysts may have elevated privileges and access to critical threat intelligence data.
The remediation implemented by the AIL Framework developers demonstrates proper security engineering practices through the application of Jinja's tojson filter, which provides context-appropriate encoding for JavaScript string contexts. This solution directly addresses the root cause by ensuring that special characters within the crawled URLs are properly escaped before insertion into the JavaScript handler, preventing the termination of JavaScript strings and subsequent code execution. The fix aligns with industry best practices for preventing XSS vulnerabilities in web applications by applying appropriate output encoding based on the target context, specifically following the principle of context-aware encoding as recommended in OWASP's XSS Prevention Cheat Sheet. This defensive programming approach ensures that even if malicious data enters the system through legitimate input mechanisms, it cannot be interpreted as executable code within the JavaScript context due to proper serialization and escaping techniques.